Search results for: linguistics , sentiment analysis, machine learning, organizations
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublicationPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublicationGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
PublicationEfficient structural reliability analysis method is crucial to solving reliability analysis of complex structural problems. High-computational cost and low-failure probability problems greatly limit the efficiency in structural reliability analysis problems, causing the safety and reliability of the structure to be questioned. In this work, a highly efficient structural reliability analysis method coupling active Kriging algorithm...
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Selecting cost-effective risk control option for advanced maritime operations; Integration of STPA-BN-Influence diagram
PublicationAdvanced maritime operations, such as remote pilotage, are vulnerable to new emergent risks due to increased system complexity and a multitude of interactions. Thus, maritime researchers this decade have combined Systems-Theoretic Process Analysis (STPA) and Bayesian Network (BN) to effectively manage these risks. Although these methods are effective in identifying hazards and analyzing risk levels, none of the STPA-BN studies...
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Induction motor bearings diagnostic indicators based on MCSA and normalized triple covariance
PublicationInduction motors are one of the most widely used electrical machines. Statistics of bearing failures of induction motors indicate, that they constitute more than 40% of induction motor damage. Therefore, bearing diagnosis is so important for trouble-free work of induction motors. The most common methods of bearing diagnosis are based on vibration signal analysis. The main disadvantage of those methods is the need for physical access...
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MCSA with Normalized Triple Covariance as a bearings diagnostic indicator in an induction motor
PublicationStatistics of bearing failures in induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is very important. Vibration methods for bearing diagnostics have one major disadvantage - they require the availability of the machine for sensors installation. This is the reason for seeking new methods based on motor supply current analysis. Diagnosis of induction motors, conducted remotely...
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Changes in the addiction prevalence in Polish population between 1990-2019: Review of available data
PublicationThe 1989 collapse of the socialist political system in Poland initiated an avalanche of modifications regarding healthcare policy resulting with new institutions and programs dedicated to monitoring and preventing addiction. In the current article, we look at the available data allowing to track changes in (1) the prevalence of exposure to addictive substances and behaviors, and (2) changes of addictions prevalence in Poland...
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Optymizm przedsiębiorców a ich postawy wobec zmian
PublicationArtykuł dotyczy postaw przedsiębiorców wobec wprowadzania zmian w zarządzanych przez nich firmach. Celem podjętych badań była weryfikacja hipotezy, że poziom optymizmu przedsiębiorcy wpływa na akceptację sytuacji zmian w organizacji i otwartość na jej wdrażanie. Badaniom kwestionariuszowym poddano przedsiębiorców działających na terenie Trójmiasta. Wykorzystano Skalę Orientacji Pozytywnej oraz adaptację Skali Postaw Pracowniczych...
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State and control system variables sensitivity to rotor asymmetry in the induction motor drive
PublicationThe aim of this paper is to undertake analysis and comparison of the closed-loop and sensorless control systems sensitivity to the broken rotor for diagnostic purposes. For the same vector control system induction motor drive analysis concerning operation with the asymmetric motor, broken rotor fault handling and operation were investigated. Reliability, range of stable operation, fault symptoms and application of diagnosis methods...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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The best practices transfer part I
PublicationThis expertise describes the possibilities of best practices implementation. These examples of best practices concern to improve the women’ entrepreneurship and were identified at the earlier stage of the project. One of the areas of activity within the QUICK IGA project was the selection of best practices related to strengthening the economic activity of women in the context of developing the competitiveness and innovation of...
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Application of modern sample-preparation techniques to the determination of chloropropanols in food samples
PublicationChloropropanols are heat-induced food toxicants that recently caused concern among industrial and scientific experts. World and European organizations related to food safety asked researchers to investigate mitigation strategies regarding these contaminants. The essential objective of this project was development of fast analytical methods enabling reliable determination and quantification of 3-monochloropropane-1,2-diol, 2-monochloropropane-1,3-diol...
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The Impact of Information and Communication Technology on the Rise of Urban Social Movements in Poland
PublicationThe chapter examines the relationship between the use of Information and Communications Technology (ITC) and the emergence of social movements focused on urban agenda in Poland. The aim is to investigate how and to what extent a growing body of smaller activist groups use opportunities provided by the ITC to achieve their political objectives. The research results indicate that Web-based media have helped to raise the profile...
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The Impact of Information and Communications Technology on the Rise of Urban Social Movements in Poland
PublicationThe chapter examines the relationship between the use of Information and Communications Technology (ITC) and the emergence of social movements focused on urban agenda in Poland. The aim is to investigate how and to what extent a growing body of smaller activist groups use opportunities provided by the ITC to achieve their political objectives. The research results indicate that Web-based media have helped to raise the profile of...
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Desirability-based optimization of dual-fuel diesel engine using acetylene as an alternative fuel
Publicationhe study examined the dual-fuel engine performance employing acetylene gas as primary fuel and diesel as pilot fuel. The engine's operational parameters were adjusted using the Box-Behnken design, and the results were recorded. The best operating settings were yielded as 81.25 % engine load, 4.48 lpm acetylene gas flow rate and the compression ratio were 18. At this optimized setting the BTE was 27.1 % and the engine emitted 360...
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Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology
PublicationLignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublicationImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Exploring the Usability and User Experience of Social Media Apps through a Text Mining Approach
PublicationThis study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics...
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Rafał Leszczyna dr hab. inż.
PeopleDr hab. Rafal Leszczyna is an associate professor at Gdansk University of Technology, Faculty of Management and Economics. He holds the M.Sc. degrees of Computer Science and Business Management. In December, 2006 he earned a Ph.D. in Computer Science, specialisation - Computer Security at the Faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. Between 2004 and 2008 he worked in the European...
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Functional safety analysis including human factors
PublicationThe article addresses selected aspects of human factors that should be taken into account during the design of safety-related functions for a complex hazardous installation and its protections. In such installations the layer of protection analysis (LOPA) methodology is often used for simplified risk analysis based on defined accident scenarios. To control the risk the safety instrumented functions (SIFs) are identified and their...
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Thin-walled frames and grids - statics and dynamics
PublicationFrames and grids assembled with thin-walled beams of open cross-section are widely applied in various civil engineering and vehicle or machine structures. Static and dynamic analysis of theses structures may be carried out by means of different models, startingfrom the classical models made of beam elements undergoing the Kirchhoff assumptions to the FE discretization of whole frame into plane elements. The former model is very...
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Adaptacyjny system sterowania ruchem drogowym
PublicationAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
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Comparative analysis of switched reluctance motor control algorithms
PublicationПредмет исследования. Развитие микропроцессорной техники и силовой электроники позволило создавать недорогие и эффективные системы управления различными электромеханическими объектами, которые ранее широко не использовались из-за сложности управления. К таким устройствам можно отнести вентильно-индукторные электрические машины. Данные машины широко применяются в различных практических разработках, например, в тяговом электроприводе,...
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Comparative analysis of switched reluctance motor control algorithms
PublicationПредмет исследования. Развитие микропроцессорной техники и силовой электроники позволило создавать недорогие и эффективные системы управления различными электромеханическими объектами, которые ранее широко не использовались из-за сложности управления. К таким устройствам можно отнести вентильно-индукторные электрические машины. Данные машины широко применяются в различных практических разработках, например, в тяговом электроприводе,...
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublicationHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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A note on the applications of artificial intelligence in the hospitality industry: preliminary results of a survey
PublicationIntelligent technologies are widely implemented in different areas of modern society but specific approaches should be applied in services. Basic relationships refer to supporting customers and people responsible for services offering for these customers. The aim of the paper is to analyze and evaluate the state-of-the art of artificial intelligence (AI) applications in the hospitality industry. Our findings show that the major...
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Exploring governance among social co-operatives: three models from Poland
PublicationThere has been overly interest regarding social enterprise and social entrepreneurship in theory and practice. In this paper the author introduces the workings of governance of small social enterprises i.e. social co-operatives, acting in most cases for the purpose of work and social integration of the marginalized, at the bottom of the pyramid of socio-economic system. The aim of this paper is to provide insights into under researched...
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Łukasz Sienkiewicz dr hab.
PeopleGraduate of the Warsaw School of Economics, habilitated doctor in the field of social sciences in the discipline of management and quality science. University Associate professor at the Department of Entrepreneurship of the Faculty of Management and Economics of the Gdańsk University of Technology and coordinator of the Center for Economic, Social and Technological Transformation (C-TEST). Chairman of the Board of the Institute...
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Modeling the Customer’s Contextual Expectations Based on Latent Semantic Analysis Algorithms
PublicationNowadays, in the age of Internet, access to open data detects the huge possibilities for information retrieval. More and more often we hear about the concept of open data which is unrestricted access, in addition to reuse and analysis by external institutions, organizations and people. It’s such information that can be freely processed, add another data (so-called remix) and then published. More and more data are available in text...
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublicationAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Comparative Study of Machining Technology Selection to Manufacture Large-Size Components of Offshore Constructions
PublicationThe focus of this paper is on process planning for large parts manufacture in systems of definite process capabilities, involving the use of multi-axis machining centres. The analysis of machining heavy mechanical components used in off-shore constructions has been carried out. Setup concepts applied and operation sequences determined in related process plans underwent studies. The paper presents in particular a reasoning approach...
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Innovations in Wastewater Treatment: Harnessing Mathematical Modeling and Computer Simulations with Cutting-Edge Technologies and Advanced Control Systems
PublicationThe wastewater treatment landscape in Central Europe, particularly in Poland, has undergone a profound transformation due to European Union (EU) integration. Fueled by EU funding and rapid technological advancements, wastewater treatment plants (WWTPs) have adopted cutting-edge control methods to adhere to EU Water Framework Directive mandates. WWTPs contend with complexities such as variable flow rates, temperature fluctuations,...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublicationDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Dariusz Dąbrowski dr hab. inż.
PeopleDariusz Dąbrowski graduated from the Faculty of Shipbuilding at Gdańsk University of Technology and in 1987 began working at the university as an assistant in the Department of Shipbuilding Industry Organization within the then Institute of Organization and Design of Production Systems. In 1990, he went on a TEMPUS scholarship from the EU and spent 14 months at the University of Sheffield, where he participated in the Master of...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Open Research DataMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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DIAGNOSTYKA ŁOŻYSK SILNIKA INDUKCYJNEGO PRZY UŻYCIU POMIARU PRĄDU ZASILAJĄCEGO I WIBRACJI
PublicationW artykule przedstawione zostały wyniki badań diagnostycznych łożysk silnika indukcyjnego z zastosowaniem metody pomiaru prądu zasilającego oraz wibracji. Poruszone zostały problemy dotyczące poszukiwania nowej metody opartej na pomiarze i analizie prądu, która w znacznym stopniu ułatwiłaby szybkie i sprawne znalezienie uszkodzenia w maszynie, bez konieczności bezpośredniego dostępu do badanego urządzenia. Zaprezentowano rezultaty...
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Ultrasonic wave propagation and digital image correlation measurements of steel bars under 3-point bending
Open Research DataThe DataSet contains the results of the mechanical behaviour of a bar under a 3-point bending test. The bar was made of steel and had a cross-section of 5.96 × 5.96 mm2 and a length of 200 mm. The three-point bending test was performed using a Zwick/Roell Z10 universal testing machine (UTM), with a distance between supports of 12 cm. The parameters...
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Acoustic emission signals in concrete beams under 3-point bending (beams #1, #2, #3)
Open Research DataThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: cement CEM I 42.5R (330 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3), water (165 kg/m3) and super-plasticizer...
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Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublicationElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublicationThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...